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init eACGM

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Tokisakix
2025-08-07 10:14:54 +08:00
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demo/sampler_torch.py Normal file
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import time
import json
from eacgm.bpf import BccBPF
from eacgm.sampler import eBPFSampler
from eacgm.collector import to_perfetto
func_sym = {
"TorchAdd": "_ZN5torch8autogradL15THPVariable_addEP7_objectS2_S2_",
"TorchSub": "_ZN5torch8autogradL15THPVariable_subEP7_objectS2_S2_",
"TorchMul": "_ZN5torch8autogradL15THPVariable_mulEP7_objectS2_S2_",
"TorchMatmul": "_ZN5torch8autogradL18THPVariable_matmulEP7_objectS2_S2_",
"TorchDiv": "_ZN5torch8autogradL15THPVariable_divEP7_objectS2_S2_",
"TorchLinear": "_ZN5torch8autogradL18THPVariable_linearEP7_objectS2_S2_",
"TorchConv2d": "_ZN5torch8autogradL18THPVariable_conv2dEP7_objectS2_S2_",
"TorchReLU": "_ZN5torch8autogradL16THPVariable_reluEP7_objectS2_S2_",
"TorchSigmoid": "_ZN5torch8autogradL19THPVariable_sigmoidEP7_objectS2_S2_",
"TorchTanh": "_ZN5torch8autogradL16THPVariable_tanhEP7_objectS2_S2_",
"TorchSoftmax": "_ZN5torch8autogradL19THPVariable_softmaxEP7_objectS2_S2_",
"TorchMSELoss": "_ZN5torch8autogradL20THPVariable_mse_lossEP7_objectS2_S2_",
"TorchBCELoss": "_ZN5torch8autogradL32THPVariable_binary_cross_entropyEP7_objectS2_S2_",
"TorchCrossEntropyLoss": "_ZN5torch8autogradL30THPVariable_cross_entropy_lossEP7_objectS2_S2_",
"TorchConvTranspose2d": "_ZN5torch8autogradL28THPVariable_conv_transpose2dEP7_objectS2_S2_",
"TorchMaxUnpool2d": "_ZN5torch8autogradL24THPVariable_max_unpool2dEP7_objectS2_S2_",
"TorchBatchNorm2d": "_ZN5torch8autogradL22THPVariable_batch_normEP7_objectS2_S2_",
"TorchAvgPool2d": "_ZN5torch8autogradL22THPVariable_avg_pool2dEP7_objectS2_S2_",
"TorchMaxPool2d": "_ZN5torch8autogradL22THPVariable_max_pool2dEP7_objectS2_S2_",
"TorchDropout": "_ZN5torch8autogradL19THPVariable_dropoutEP7_objectS2_S2_",
"TorchEmbedding": "_ZN5torch8autogradL21THPVariable_embeddingEP7_objectS2_S2_",
"TorchLSTM": "_ZN5torch8autogradL16THPVariable_lstmEP7_objectS2_S2_",
"TorchAdaptiveMaxPool2d": "_ZN5torch8autogradL31THPVariable_adaptive_max_pool2dEP7_objectS2_S2_",
"TorchAdaptiveAvgPool2d": "_ZN5torch8autogradL31THPVariable_adaptive_avg_pool2dEP7_objectS2_S2_",
}
template = """
int <TorchSym>Entry(struct pt_regs *ctx){
u64 ts = bpf_ktime_get_ns();
bpf_trace_printk("%ld@start@<TorchFunc>\\n", ts);
return 0;
};
int <TorchSym>Exit(struct pt_regs *ctx){
u64 ts = bpf_ktime_get_ns();
bpf_trace_printk("%ld@end@<TorchFunc>\\n", ts);
return 0;
};
"""
text = ""
for func in func_sym:
sym = func_sym[func]
text += template.replace("<TorchSym>", sym).replace("<TorchFunc>", func)
bpf = BccBPF("TorcheBPF", text, ["-w"])
attach_config = [
{
"name": "TorchSampler",
"exe_path": [
"/home/txx/data/miniconda3/envs/eACGM/lib/python3.12/site-packages/torch/./lib/libtorch_python.so",
],
"exe_sym": [
"_ZN5torch8autogradL15THPVariable_addEP7_objectS2_S2_",
"_ZN5torch8autogradL15THPVariable_subEP7_objectS2_S2_",
"_ZN5torch8autogradL15THPVariable_mulEP7_objectS2_S2_",
"_ZN5torch8autogradL18THPVariable_matmulEP7_objectS2_S2_",
"_ZN5torch8autogradL15THPVariable_divEP7_objectS2_S2_",
"_ZN5torch8autogradL18THPVariable_linearEP7_objectS2_S2_",
"_ZN5torch8autogradL18THPVariable_conv2dEP7_objectS2_S2_",
"_ZN5torch8autogradL16THPVariable_reluEP7_objectS2_S2_",
"_ZN5torch8autogradL19THPVariable_sigmoidEP7_objectS2_S2_",
"_ZN5torch8autogradL16THPVariable_tanhEP7_objectS2_S2_",
"_ZN5torch8autogradL19THPVariable_softmaxEP7_objectS2_S2_",
"_ZN5torch8autogradL20THPVariable_mse_lossEP7_objectS2_S2_",
"_ZN5torch8autogradL32THPVariable_binary_cross_entropyEP7_objectS2_S2_",
"_ZN5torch8autogradL30THPVariable_cross_entropy_lossEP7_objectS2_S2_",
"_ZN5torch8autogradL28THPVariable_conv_transpose2dEP7_objectS2_S2_",
"_ZN5torch8autogradL24THPVariable_max_unpool2dEP7_objectS2_S2_",
"_ZN5torch8autogradL22THPVariable_batch_normEP7_objectS2_S2_",
"_ZN5torch8autogradL22THPVariable_avg_pool2dEP7_objectS2_S2_",
"_ZN5torch8autogradL22THPVariable_max_pool2dEP7_objectS2_S2_",
"_ZN5torch8autogradL19THPVariable_dropoutEP7_objectS2_S2_",
"_ZN5torch8autogradL21THPVariable_embeddingEP7_objectS2_S2_",
"_ZN5torch8autogradL16THPVariable_lstmEP7_objectS2_S2_",
"_ZN5torch8autogradL31THPVariable_adaptive_max_pool2dEP7_objectS2_S2_",
"_ZN5torch8autogradL31THPVariable_adaptive_avg_pool2dEP7_objectS2_S2_",
]
},
]
sampler = eBPFSampler(bpf)
sampler.run(attach_config)
states = []
while True:
try:
samples = sampler.sample(time_stamp=1)
states += samples
# for sample in samples:
# print(sample)
# print("---")
except KeyboardInterrupt:
break
sampler.close()
collector = to_perfetto(states)
json.dump(collector, open("torch.json", "w", encoding="utf-8"), indent=4)